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An Overview on the Latest Nature-Inspired and Metaheuristics-Based Image Registration Algorithms

J. Santamaría, M. L. Rivero-Cejudo, M. A. Martos-Fernández, F. Roca

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Tags: Computer science, Computer vision, Evolutionary Computations, Image registration, Metaheuristics, Neural and Evolutionary Computing, Overview

May 4, 2020 by hgpu

Tools for GPU Computing – Debugging and Performance Analysis of Heterogenous HPC Applications

Michael Knobloch, Bernd Mohr

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Tags: Computer science, CUDA, HPC, nVidia, OpenACC, OpenCL, Performance

May 3, 2020 by hgpu

AutoParBench: A Unified Test Framework for OpenMP-based Parallelizers

Gleison Souza Diniz Mendonça, Chunhua Liao, Fernando Magno Quintão Pereira

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Tags: Benchmarking, Code generation, Computer science, OpenMP, Package

May 3, 2020 by hgpu

Leveraging Data-Flow Information for Efficient Scheduling of Task-Parallel Programs on Heterogeneous Systems

Osman Seckin Simsek

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Tags: Computer science, FPGA, Heterogeneous systems, nVidia, nVidia GeForce GTX Titan V, OpenCL, performance portability, Tesla K20, Thesis

May 3, 2020 by hgpu

Tools for Reduced Precision Computation: A Survey

Stefano Cherubin, Giovanni Agosta

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Tags: Approximate computing and storage, Computer science, CUDA, HPC, Mixed precision, nVidia, OpenCL, Precision, survey

May 3, 2020 by hgpu

86 PFLOPS Deep Potential Molecular Dynamics simulation of 100 million atoms with ab initio accuracy

Denghui Lu, Han Wang, Mohan Chen, Jiduan Liu, Lin Lin, Roberto Car, Weinan E, Weile Jia, Linfeng Zhang

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Tags: Computational Physics, CUDA, Heterogeneous systems, Molecular dynamics, Neural networks, nVidia, Package, Physics, Python, Tesla V100

May 3, 2020 by hgpu

cuda-kat: The CUDA Kernel Author’s Toolkit

Eyal Rozenberg

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Tags: cpp, CUDA, library, nVidia, Package

May 2, 2020 by epk

Automatic Parallelization for Heterogeneous Embedded Systems

Rokiatou Diarra

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Tags: Computer science, CUDA, Heterogeneous systems, nVidia, nVidia Quadro M 2000 M, nVidia Tegra TX1, OpenACC, OpenCL, Thesis

April 26, 2020 by hgpu

Accelerating Winograd Convolutions using Symbolic Computation and Meta-programming

Arya Mazaheri, Tim Beringer, Matthew Moskewicz, Felix Wolf, Ali Jannesari

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Tags: AMD Radeon RX 580, ATI, Code generation, Computer science, CUDA, Deep learning, Neural networks, nVidia, nVidia GeForce GTX 1080 Ti, OpenCL, Performance, performance portability, Symbolic Computation, Vulkan

April 26, 2020 by hgpu

Evaluating FPGA Accelerator Performance with a Parameterized OpenCL Adaptation of the HPCChallenge Benchmark Suite

Marius Meyer, Tobias Kenter, Christian Plessl

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Tags: Benchmarking, Computer science, FPGA, HLS, OpenCL, Package

April 26, 2020 by hgpu

GEVO: GPU Code Optimization using Evolutionary Computation

Jhe-Yu Liou, Xiaodong Wang, Stephanie Forrest, Carole-Jean Wu

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Tags: Computer science, CUDA, Evolutionary Computations, Machine learning, Neural and Evolutionary Computing, nVidia, Package, PTX, Tesla P100

April 26, 2020 by hgpu

Cpp-Taskflow: A General-purpose Parallel and Heterogeneous Task Programming System at Scale

Tsung-Wei Huang, Dian-Lun Lin, Yibo Lin, Chun-Xun Lin

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Tags: Computer science, CUDA, Heterogeneous systems, Machine learning, nVidia, nVidia GeForce RTX 2080, Package, Performance

April 26, 2020 by hgpu

torchPDLP: Primal-Dual Linear Programming in PyTorch. In collaboration with AMD and IPAM

Accelerating a Linear Programming Algorithm on AMD GPUs

Benchmarks for Dissecting CPU-GPU Unified Physical Memory on AMD MI300A APUs

Dissecting CPU-GPU Unified Physical Memory on AMD MI300A APUs

kvcached: Elastic KV cache for dynamic GPU sharing and efficient multi-LLM inference

Towards Efficient and Practical GPU Multitasking in the Era of LLM

Bandicoot: C++ library for GPU accelerated linear algebra

Bandicoot: A Templated C++ Library for GPU Linear Algebra

Luthier: Bridging Auto-Tuning and Vendor Libraries for Efficient Deep Learning Inference

Fused Kernel Library (FKL)

The Fused Kernel Library: A C++ API to Develop Highly-Efficient GPU Libraries

GPUHammer: Rowhammer Attacks on GPU Memories are Practical

Block: Balance Loader of LLM Serving with Context, Knowledge and Predictive Scheduling

Block: Balancing Load in LLM Serving with Context, Knowledge and Predictive Scheduling

SIGMo: Scalable Isomorphism Graph Matching on GPUs

SIGMo: High-Throughput Batched Subgraph Isomorphism on GPUs for Molecular Matching

DGEMM without FP64 Arithmetic - using FP64 Emulation and FP8 Tensor Cores with Ozaki Scheme

DGEMM without FP64 Arithmetic – using FP64 Emulation and FP8 Tensor Cores with Ozaki Scheme

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high performance computing on graphics processing units: hgpu.org

Applications

An Overview on the Latest Nature-Inspired and Metaheuristics-Based Image Registration Algorithms

Tools for GPU Computing – Debugging and Performance Analysis of Heterogenous HPC Applications

AutoParBench: A Unified Test Framework for OpenMP-based Parallelizers

Leveraging Data-Flow Information for Efficient Scheduling of Task-Parallel Programs on Heterogeneous Systems

Tools for Reduced Precision Computation: A Survey

86 PFLOPS Deep Potential Molecular Dynamics simulation of 100 million atoms with ab initio accuracy

cuda-kat: The CUDA Kernel Author’s Toolkit

Automatic Parallelization for Heterogeneous Embedded Systems

Accelerating Winograd Convolutions using Symbolic Computation and Meta-programming

Evaluating FPGA Accelerator Performance with a Parameterized OpenCL Adaptation of the HPCChallenge Benchmark Suite

GEVO: GPU Code Optimization using Evolutionary Computation

Cpp-Taskflow: A General-purpose Parallel and Heterogeneous Task Programming System at Scale

Recent source codes

torchPDLP: Primal-Dual Linear Programming in PyTorch. In collaboration with AMD and IPAM

Benchmarks for Dissecting CPU-GPU Unified Physical Memory on AMD MI300A APUs

kvcached: Elastic KV cache for dynamic GPU sharing and efficient multi-LLM inference

Bandicoot: C++ library for GPU accelerated linear algebra

Luthier: Bridging Auto-Tuning and Vendor Libraries for Efficient Deep Learning Inference

Fused Kernel Library (FKL)

GPUHammer: Rowhammer Attacks on GPU Memories are Practical

Block: Balance Loader of LLM Serving with Context, Knowledge and Predictive Scheduling

SIGMo: Scalable Isomorphism Graph Matching on GPUs

DGEMM without FP64 Arithmetic - using FP64 Emulation and FP8 Tensor Cores with Ozaki Scheme

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